We are seeking an exceptional hands-on technical leader with a proven track record to join the U.S. Bank Digital Innovation team. This team is responsible for advancing the applied use of Artificial Intelligence and Machine Learning at U.S. Bank, defining the AI strategy and showcasing the potential for AI through early-stage solutions (e.g. "art of the possible") as well as supporting major enterprise-wide AI/ML initiatives.
Take on some of technology's greatest challenges and make a significant impact to millions of users by leveraging the bank's unique data assets to drive groundbreaking work in AI/ML that can be applied at massive scale across U.S. Bank lines of business. Work alongside digital and innovation leadership teams in a newly renovated office space downtown.
Distinguished Engineers are recognized as experts in one or more domains within U.S. Bank and across the industry. They represent the senior technical experts within the organization and have a strong track record of growing and influencing others.
As a Distinguished Engineer, you will be responsible helping to shape the go-forward AI strategy of the organization; working with senior leaders, vendors, and partners to influence business and technology roadmaps and the adoption of AI across the enterprise. In addition, you will teach, mentor, and grow other domain experts within the organization. Distinguished Engineers will connect teams to one another in a spirit of collaboration and will champion opportunities to make teams more efficient. This is an executive-level individual contributor role requiring excellent acumen in using technical prowess and ingenuity when representing U.S. Bank's AI/ML capabilities in internal and external forums.
The ideal candidate will have previously served in a leadership capacity in the use of AI/ML. He/She will play a diverse and far-reaching role in the organization, providing leadership and influencing adoption of technical solutions, strategies and design patterns across multiple teams and stakeholders.
Graduate degree (PhD preferred) in a quantitative discipline, e.g. Computer Science, Mathematics, Operations Research, Data Science, and 8 years of experience in a highly quantitative position.
Comprehensive knowledge of modern and cutting-edge ML techniques, tools, and best practices
5 years of hands-on experience developing and operationalization advanced machine learning with track record of success and proven outcomes.
Ability to develop and debug in Python, Java, C or C . Proficient in git version control. R and Matlab are also useful.
Extensive experience with machine learning APIs and computational packages (e.g. TensorFlow, Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas).
Experience with big data architecture and distributed computing tools (e.g. Map/Reduce, Hadoop, Hive, Spark, Kafka, etc.)
Ability to design and evaluate key metrics of your model's performance which are aligned with business goals.
Proven track record of strong verbal/written communication and presentation skills, including an ability to effectively communicate with both business and technical teams.
Advanced time series analysis, natural language understanding, NLP or financial engineering background
Strong background in Mathematics and Statistics
Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal or open-source contribution
Familiarity with big-data technologies such as Maven, Hadoop, Spark, SparkML, etc.
Experience with distributed systems, GPUs and cloud-based training of deep neural networks
High enthusiasm, integrity, ingenuity, results-orientation, self-motivation, and resourcefulness in a fast-paced environment
Knowledge in Reinforcement Learning or Evolutionary Learning